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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer I - **Company:** Gen Digital - **Location:** Mountain View, CA, United States - **Experience:** Experienced - **Salary:** $176,000.0 - $191,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Data Analysis, BigQuery, Cloud Database, Customer Data Management, Data Transformation, Data Mining, Database Queries, Python (Programming Language), Machine Learning, Recommender Systems, Azure Machine Learning, Supervised Learning, Data Processing, Feature Engineering, Apache Spark, Scikit Learn, Information Technology, Data Analytics, Software Version Control - **Published:** June 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=081b170085ad111e ## About the Role Do you have experience in Version control systems?, Do you have a Master's degree?, Experience with recommender systems, uplift modeling, contextual bandits, pricing, or lifecycle personalization is a plus., * Degree requirements are flexible. A technical degree in Computer Science, Data Science, Statistics, Mathematics, Operations Research, Economics, Engineering, or a related field is helpful, but equivalent practical experience is equally valued. A Master's or PhD in a quantitative field is a plus, but not required. * Applied ML and model development: Two or more years of professional experience in applied machine learning, data science, ML engineering, applied statistics, or a related field, including experience building and evaluating models with real-world data. * Data analytics: Experience analyzing behavioral, transactional, product, marketing, or customer data and translating findings into practical insights or recommendations. * Experimentation: Experience defining success metrics, analyzing experiments, evaluating model performance, and interpreting business impact. * Collaborative delivery: Experience working with engineering, product, analytics, or business partners to deploy or apply data-driven solutions. * Relevant specialization: Experience with personalization, recommendation, ranking, uplift modeling, causal inference, contextual bandits, pricing, or lifecycle decisioning is a plus. * Machine learning and modeling: Strong Python skills and practical knowledge of supervised learning, model selection, hyperparameter tuning, evaluation, and performance analysis. * Data processing and feature engineering: Strong SQL skills and experience using platforms such as BigQuery, Spark, or similar tools for data extraction, cleaning, preprocessing, exploration, and feature development. * Analytics and experimentation: Strong analytical and statistical reasoning, including A/B testing, holdout design, statistical significance, incrementally, and business-impact measurement. * Technical tools and workflows: Familiarity with common ML libraries, cloud data or ML platforms, version control, and AI-assisted development tools. * Ownership mindset: Takes responsibility for assigned work, follows through on commitments, and proactively addresses issues. * Business-impact orientation: Connects modeling and analysis to customer experience and measurable outcomes. * AI-first builder mindset: Enjoys modeling, analyzing, automating, and shipping while using AI tools to improve productivity and quality. * Growth mindset: Learns quickly, seeks feedback, and continuously develops technical and business knowledge. * Clear, collaborative communication: Communicates ideas, assumptions, results, and challenges effectively with technical and non-technical partners. ## Description Our team is a core part of Gen's AI transformation. We build machine learning solutions that improve customer growth, retention, personalization, pricing, recommendations, billing success, and long-term customer value. We are looking for a hands-on AI / Machine Learning Engineer I to build models, analyze customer and product data, evaluate experiments, and help deploy practical ML solutions. You will own well-scoped projects and collaborate with experienced team members and cross-functional partners., * Applied ML ownership: Own well-defined machine learning projects from data exploration and model development through validation, deployment, and iteration. * Model development: Build and improve predictive, recommendation, ranking, segmentation, uplift, and customer-value models for customer personalization and decisioning. * Data and feature development: Prepare datasets, define modeling targets, develop features, and ensure data quality for training and evaluation. * Experimentation and measurement: Design and analyze A/B tests, holdouts, and offline evaluations to measure model performance and business impact. * Deployment and collaboration: Work with engineering, product, analytics, and business partners to integrate models into production and improve them based on results and feedback. * AI-first development: Use AI coding assistants, automation, and reusable tools to improve the speed, quality, and consistency of modeling and analytical workflows. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [Bringing the power of AI to your application.](https://www.wearedevelopers.com/videos/1010-bringing-the-power-of-ai-to-your-application) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [Beyond Autocomplete: Local AI Code Completion Demystified](https://www.wearedevelopers.com/videos/961-beyond-autocomplete-local-ai-code-completion-demystified) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)